{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3-final"
  },
  "orig_nbformat": 2,
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.8.3 64-bit (conda)",
   "metadata": {
    "interpreter": {
     "hash": "73e03da126b73bfff3642ec5261d56fa25c444ea595de51041687efaa60dda41"
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from turbine import Turbine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "myTurbine = Turbine()\n",
    "myTurbine.stage.solve_stage()\n",
    "myTurbine.stage.get_data()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "抽汽流量： 8.52518010539425\n疏水流量： 8.52518010539425\n抽汽\n0.23164005   409.0 \n3113.9   8.525180105394252\n进口\n-1e-06   189.20000000000005 \n809.73   130.0\n出口\n-1e-06   220.0 \n947.89   130.0\n疏水\n-1e-06   224.0 \n964.11   8.525180105394252\n下级疏水\n-1e-06   -274.15 \n-0.001   0.0\n补水\n"
     ]
    }
   ],
   "source": [
    "reheater = myTurbine.reheat.reheater_list[0]\n",
    "reheater.verbose=True\n",
    "reheater.extraction[2] = 3113.9 * 1000\n",
    "reheater.extraction[0] = 406.9 + 273.15\n",
    "reheater.inlet[2] = 809.73 * 1000\n",
    "reheater.outlet[2] = 947.89 * 1000\n",
    "reheater.trap[2] = 964.11 * 1000\n",
    "reheater.solve_heater()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "33716976.864534065   28955000.0      0.16446129734187756\n",
      "33592310.31736155   28955000.0      0.16015576989678978\n",
      "33467518.742704514   28955000.0      0.15584592445879863\n",
      "33342602.140562996   28955000.0      0.15153176102790525\n",
      "33217560.51093698   28955000.0      0.1472132796041091\n",
      "33092393.853826463   28955000.0      0.14289048018741024\n",
      "32967102.16923144   28955000.0      0.13856336277780834\n",
      "32841685.45715192   28955000.0      0.13423192737530373\n",
      "32716143.71758791   28955000.0      0.12989617397989675\n",
      "32590476.9505394   28955000.0      0.12555610259158692\n",
      "32464685.156006385   28955000.0      0.12121171321037419\n",
      "32338768.33398886   28955000.0      0.11686300583625835\n",
      "32212726.48448685   28955000.0      0.11250998046924027\n",
      "32086559.607500326   28955000.0      0.1081526371093188\n",
      "31960267.703029323   28955000.0      0.10379097575649537\n",
      "31833850.771073803   28955000.0      0.09942499641076855\n",
      "31707308.8116338   28955000.0      0.0950546990721395\n",
      "31580641.82470928   28955000.0      0.0906800837406072\n",
      "31453849.81030026   28955000.0      0.08630115041617202\n",
      "31326932.768406767   28955000.0      0.081917899098835\n",
      "31199890.69902874   28955000.0      0.07753032978859407\n",
      "31072723.602166243   28955000.0      0.07313844248545132\n",
      "30945431.477819234   28955000.0      0.06874223718940543\n",
      "30818014.32598773   28955000.0      0.06434171390045693\n",
      "30690472.14667172   28955000.0      0.05993687261860542\n",
      "30562804.939871214   28955000.0      0.0555277133438513\n",
      "30435012.7055862   28955000.0      0.05111423607619405\n",
      "30307095.4438167   28955000.0      0.04669644081563457\n",
      "30179053.1545627   28955000.0      0.04227432756217236\n",
      "30050885.8378242   28955000.0      0.03784789631580726\n",
      "29922593.493601184   28955000.0      0.033417147076538915\n",
      "29794188.778517444   28955000.0      0.02898251695795005\n",
      "29665701.007094294   28955000.0      0.024545018376594504\n",
      "29537127.996871553   28955000.0      0.020104575958264665\n",
      "29408466.100684095   28955000.0      0.01566106374319099\n",
      "29279711.68855475   28955000.0      0.011214356365213224\n",
      "[-1.          0.62521233  0.75380759  0.80917293  0.85575446  0.86962785\n",
      "  0.34        0.34      ]\n"
     ]
    }
   ],
   "source": [
    "myTurbine = Turbine()\n",
    "myTurbine.init_data()\n",
    "myTurbine.stage.solve()\n",
    "print(myTurbine.stage.EffStage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "抽汽流量： 8.61312298093653\n疏水流量： 8.61312298093653\n抽汽\n2.82186   409.0 \n3113.9   8.613122980936533\n进口\n-1e-06   189.20000000000005 \n803.8654699475609   130.0\n出口\n-1e-06   220.0 \n943.5786700422428   130.0\n疏水\n-1e-06   224.0 \n962.1388180164951   8.613122980936533\n下级疏水\n-1e-06   -274.15 \n-0.001   0.0\n补水\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "抽汽\n2.82186   409.0 \n3113.9   8.613122980936533\n进口\n-1e-06   189.20000000000005 \n803.8654699475609   130.0\n出口\n-1e-06   220.0 \n943.5786700422428   130.0\n疏水\n-1e-06   224.0 \n962.1388180164951   8.613122980936533\n下级疏水\n-1e-06   -274.15 \n-0.001   0.0\n补水\n"
     ]
    }
   ],
   "source": [
    "reheater.print_info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "1\n抽汽\n2.82186   409.0 \n3255.052839466527   8.082895177338049\n进口\n-1e-06   189.20000000000005 \n803.8654699475609   130.0\n出口\n-1e-06   220.0 \n943.5786700422428   130.0\n疏水\n-1e-06   224.0 \n962.1388180164951   8.082895177338049\n下级疏水\n-1e-06   -274.15 \n-0.001   0.0\n补水\n2\n抽汽\n1.4616   334.5 \n3115.0893401329586   3.862757478127156\n进口\n-1e-06   158.10000000000002 \n667.2245372737602   130.0\n出口\n-1e-06   189.20000000000005 \n803.8654699475609   130.0\n疏水\n-1e-06   193.20000000000005 \n821.7276523458695   15.008652655465156\n下级疏水\n-1e-06   224.0 \n962.1388180164951   8.082895177338049\n补水\n3\n抽汽\n0.8678   277.30000000000007 \n3006.773243798134   4.968760497688697\n进口\n-1e-06   139.60000000000002 \n587.446198782582   74.6225868468461\n出口\n-1e-06   158.10000000000002 \n667.2245372737602   130.0\n疏水\n-1e-06   -274.15 \n-0.001   0.0\n下级疏水\n-1e-06   193.20000000000005 \n821.7276523458695   15.008652655465156\n补水\n4\n抽汽\n0.4466   208.40000000000003 \n2876.300211856415   3.9481638778283727\n进口\n-1e-06   112.0 \n469.8818368085788   74.6225868468461\n出口\n-1e-06   139.60000000000002 \n587.446198782582   74.6225868468461\n疏水\n-1e-06   144.60000000000002 \n608.917949256021   3.9481638778283727\n下级疏水\n-1e-06   -274.15 \n-0.001   0.0\n补水\n5\n抽汽\n0.196   133.40000000000003 \n2734.8425169160178   5.1072887687088135\n进口\n-1e-06   74.70000000000005 \n312.77157269029874   74.6225868468461\n出口\n-1e-06   112.0 \n469.8818368085788   74.6225868468461\n疏水\n-1e-06   116.0 \n486.8336662791459   9.055452646537184\n下级疏水\n-1e-06   144.60000000000002 \n608.917949256021   3.9481638778283727\n补水\n6\n抽汽\n0.0508   81.80000000000001 \n2658.740053166342   6.70713420030892\n进口\n0.0044   30.670000000000016 \n2556.759839363229   58.86\n出口\n-1e-06   74.70000000000005 \n312.77157269029874   74.6225868468461\n疏水\n-1e-06   79.70000000000005 \n333.7528691750542   15.7625868468461\n下级疏水\n-1e-06   116.0 \n486.8336662791459   9.055452646537184\n补水\n"
     ]
    }
   ],
   "source": [
    "for i, reheater in enumerate(myTurbine.reheat.reheater_list):\n",
    "    print(i+1)\n",
    "    reheater.print_info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "trap = [reheater.trap for reheater in myTurbine.reheat.reheater_list]\n",
    "trap_ = [reheater.trap_ for reheater in myTurbine.reheat.reheater_list]\n",
    "extraction = [reheater.extraction for reheater in myTurbine.reheat.reheater_list]\n",
    "inlet = [reheater.inlet for reheater in myTurbine.reheat.reheater_list]\n",
    "outlet = [reheater.outlet for reheater in myTurbine.reheat.reheater_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "trap = pd.DataFrame(np.array(trap), columns=['p', 't', 'h', 'd'])\n",
    "trap_ = pd.DataFrame(np.array(trap_), columns=['p', 't', 'h', 'd'])\n",
    "extraction = pd.DataFrame(np.array(extraction), columns=['p', 't', 'h', 'd'])\n",
    "inlet = pd.DataFrame(np.array(inlet), columns=['p', 't', 'h', 'd'])\n",
    "outlet = pd.DataFrame(np.array(outlet), columns=['p', 't', 'h', 'd'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "     p       t           h          d\n",
       "0 -1.0  224.00  962.138818   8.082895\n",
       "1 -1.0  193.20  821.727652  15.008653\n",
       "2 -1.0 -274.15   -0.001000   0.000000\n",
       "3 -1.0  144.60  608.917949   3.948164\n",
       "4 -1.0  116.00  486.833666   9.055453\n",
       "5 -1.0   79.70  333.752869  15.762587"
      ],
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>p</th>\n      <th>t</th>\n      <th>h</th>\n      <th>d</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>-1.0</td>\n      <td>224.00</td>\n      <td>962.138818</td>\n      <td>8.082895</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>-1.0</td>\n      <td>193.20</td>\n      <td>821.727652</td>\n      <td>15.008653</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>-1.0</td>\n      <td>-274.15</td>\n      <td>-0.001000</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-1.0</td>\n      <td>144.60</td>\n      <td>608.917949</td>\n      <td>3.948164</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>-1.0</td>\n      <td>116.00</td>\n      <td>486.833666</td>\n      <td>9.055453</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>-1.0</td>\n      <td>79.70</td>\n      <td>333.752869</td>\n      <td>15.762587</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 27
    }
   ],
   "source": [
    "trap['t'] -= 273.15\n",
    "trap['h'] /= 1000\n",
    "trap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "\n",
    "data = pd.DataFrame(myTurbine.stage.data, columns=['p','t','h','d','h_'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['t'] = data['t'] - 273.15\n",
    "data['d'] = data['d'] / 3.6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "           p       t             h          d            h_\n",
       "0  8830000.0  261.85  3.476709e+06  36.111111 -1.000000e+00\n",
       "1  2821860.0  135.85  3.255053e+06  36.111111  3.122179e+06\n",
       "2  1461600.0   61.35  3.115089e+06  31.888542  3.069377e+06\n",
       "3   867800.0    4.15  3.006773e+06  30.836341  2.981229e+06\n",
       "4   446600.0  -64.75  2.876300e+06  29.451921  2.854308e+06\n",
       "5   196000.0 -139.75  2.734843e+06  28.364230  2.713636e+06\n",
       "6    50800.0 -191.35  2.658740e+06  19.457210  2.511012e+06\n",
       "7     4400.0 -242.48  2.539776e+06  16.350000  2.308847e+06"
      ],
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>p</th>\n      <th>t</th>\n      <th>h</th>\n      <th>d</th>\n      <th>h_</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>8830000.0</td>\n      <td>261.85</td>\n      <td>3.476709e+06</td>\n      <td>36.111111</td>\n      <td>-1.000000e+00</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2821860.0</td>\n      <td>135.85</td>\n      <td>3.255053e+06</td>\n      <td>36.111111</td>\n      <td>3.122179e+06</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1461600.0</td>\n      <td>61.35</td>\n      <td>3.115089e+06</td>\n      <td>31.888542</td>\n      <td>3.069377e+06</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>867800.0</td>\n      <td>4.15</td>\n      <td>3.006773e+06</td>\n      <td>30.836341</td>\n      <td>2.981229e+06</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>446600.0</td>\n      <td>-64.75</td>\n      <td>2.876300e+06</td>\n      <td>29.451921</td>\n      <td>2.854308e+06</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>196000.0</td>\n      <td>-139.75</td>\n      <td>2.734843e+06</td>\n      <td>28.364230</td>\n      <td>2.713636e+06</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>50800.0</td>\n      <td>-191.35</td>\n      <td>2.658740e+06</td>\n      <td>19.457210</td>\n      <td>2.511012e+06</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>4400.0</td>\n      <td>-242.48</td>\n      <td>2.539776e+06</td>\n      <td>16.350000</td>\n      <td>2.308847e+06</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 10
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils import PropsSI, PhaseSI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = PropsSI('S', 'H', 2735500,'P', 0.196*1000000, 'Water')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "h_ = PropsSI('H', 'P', 0.0508*1000000, 'S', s, 'Water')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "7209.180208753239"
      ]
     },
     "metadata": {},
     "execution_count": 11
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "2511585.4141049464"
      ]
     },
     "metadata": {},
     "execution_count": 12
    }
   ],
   "source": [
    "h_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "{'高加数目': 2.0,\n",
       " '有无除氧器': 1.0,\n",
       " '低加数目': 3.0,\n",
       " '主蒸汽流量': 130.0,\n",
       " '主蒸汽温度': 808.15,\n",
       " '主蒸汽压力': 8830000.0,\n",
       " '调节级后压力': -1.0,\n",
       " '调节级后温度': -1.0,\n",
       " '排气压力': 4400.0,\n",
       " '排气温度': 303.82,\n",
       " '排气流量': 58.86,\n",
       " '电功率': 130000000,\n",
       " '锅炉给水流量': 130,\n",
       " '锅炉给水压力': -1,\n",
       " '锅炉给水温度': 493.15,\n",
       " '机械效率': -1.0,\n",
       " '电机效率': -1.0,\n",
       " '凝结水温度': 303.82,\n",
       " '凝结水流量': 58.86,\n",
       " '循环水进口温度': 293.15,\n",
       " '循环水出口温度': 298.15,\n",
       " '汽耗率': -1.0,\n",
       " '热耗率': -1.0,\n",
       " '冷却水温升': -1.0,\n",
       " '凝结水过冷度': -1.0,\n",
       " '冷却水端差': -1.0,\n",
       " '对数平均温差': -1.0,\n",
       " '整机效率': -1.0,\n",
       " '抽汽压力_1': 2820000.0,\n",
       " '抽汽温度_1': 682.15,\n",
       " '抽汽流量_1': -1.0,\n",
       " '进口温度_1': -1.0,\n",
       " '进口流量_1': -1.0,\n",
       " '出口温度_1': 493.15,\n",
       " '出口流量_1': -1.0,\n",
       " '疏水温度_1': 497.15,\n",
       " '疏水流量_1': -1.0,\n",
       " '抽汽压力_2': 1460000.0,\n",
       " '抽汽温度_2': 607.65,\n",
       " '抽汽流量_2': -1.0,\n",
       " '进口温度_2': -1.0,\n",
       " '进口流量_2': -1.0,\n",
       " '出口温度_2': 462.34999999999997,\n",
       " '出口流量_2': -1.0,\n",
       " '疏水温度_2': 466.34999999999997,\n",
       " '疏水流量_2': -1.0,\n",
       " '抽汽压力_3': 870000.0,\n",
       " '抽汽温度_3': 550.45,\n",
       " '抽汽流量_3': -1.0,\n",
       " '进口温度_3': -1.0,\n",
       " '进口流量_3': -1.0,\n",
       " '出口温度_3': 431.25,\n",
       " '出口流量_3': -1.0,\n",
       " '疏水温度_3': -1.0,\n",
       " '疏水流量_3': -1.0,\n",
       " '抽汽压力_4': 450000.0,\n",
       " '抽汽温度_4': 481.54999999999995,\n",
       " '抽汽流量_4': -1.0,\n",
       " '进口温度_4': -1.0,\n",
       " '进口流量_4': -1.0,\n",
       " '出口温度_4': 412.75,\n",
       " '出口流量_4': -1.0,\n",
       " '疏水温度_4': 417.75,\n",
       " '疏水流量_4': -1.0,\n",
       " '抽汽压力_5': 200000.0,\n",
       " '抽汽温度_5': 406.54999999999995,\n",
       " '抽汽流量_5': -1.0,\n",
       " '进口温度_5': -1.0,\n",
       " '进口流量_5': -1.0,\n",
       " '出口温度_5': 385.15,\n",
       " '出口流量_5': -1.0,\n",
       " '疏水温度_5': 389.15,\n",
       " '疏水流量_5': -1.0,\n",
       " '抽汽压力_6': 50000.0,\n",
       " '抽汽温度_6': 354.95,\n",
       " '抽汽流量_6': -1.0,\n",
       " '进口温度_6': -1.0,\n",
       " '进口流量_6': -1.0,\n",
       " '出口温度_6': 347.84999999999997,\n",
       " '出口流量_6': -1.0,\n",
       " '疏水温度_6': 352.84999999999997,\n",
       " '疏水流量_6': -1.0,\n",
       " '抽汽压力_7': -1.0,\n",
       " '抽汽温度_7': -1.0,\n",
       " '抽汽流量_7': -1.0,\n",
       " '进口温度_7': -1.0,\n",
       " '进口流量_7': -1.0,\n",
       " '出口温度_7': -1.0,\n",
       " '出口流量_7': -1.0,\n",
       " '疏水温度_7': -1.0,\n",
       " '疏水流量_7': -1.0,\n",
       " '供热抽汽位置_1': 1.0,\n",
       " '供热抽汽流量_1': 7.2,\n",
       " '供热抽汽温度_1': 680.05,\n",
       " '供热抽汽压力_1': 2820000.0,\n",
       " '供热抽汽位置_2': 5.0,\n",
       " '供热抽汽流量_2': 27.0,\n",
       " '供热抽汽温度_2': 406.54999999999995,\n",
       " '供热抽汽压力_2': 200000.0,\n",
       " '供热抽汽位置_3': -1.0,\n",
       " '供热抽汽流量_3': -1.0,\n",
       " '供热抽汽温度_3': -1.0,\n",
       " '供热抽汽压力_3': -1.0,\n",
       " '级末压力_1': 8830000.0,\n",
       " '级末温度_1': 808.15,\n",
       " '级末比焓_1': -1.0,\n",
       " '级末理想比焓_1': -1.0,\n",
       " '级内等效流量_1': -1.0,\n",
       " '级段效率_1': -1.0,\n",
       " '级末压力_2': 2820000.0,\n",
       " '级末温度_2': 682.15,\n",
       " '级末比焓_2': -1.0,\n",
       " '级末理想比焓_2': -1.0,\n",
       " '级内等效流量_2': -1.0,\n",
       " '级段效率_2': -1.0,\n",
       " '级末压力_3': 1460000.0,\n",
       " '级末温度_3': 607.65,\n",
       " '级末比焓_3': -1.0,\n",
       " '级末理想比焓_3': -1.0,\n",
       " '级内等效流量_3': -1.0,\n",
       " '级段效率_3': -1.0,\n",
       " '级末压力_4': 870000.0,\n",
       " '级末温度_4': 550.45,\n",
       " '级末比焓_4': -1.0,\n",
       " '级末理想比焓_4': -1.0,\n",
       " '级内等效流量_4': -1.0,\n",
       " '级段效率_4': -1.0,\n",
       " '级末压力_5': 450000.0,\n",
       " '级末温度_5': 481.54999999999995,\n",
       " '级末比焓_5': -1.0,\n",
       " '级末理想比焓_5': -1.0,\n",
       " '级内等效流量_5': -1.0,\n",
       " '级段效率_5': -1.0,\n",
       " '级末压力_6': 200000.0,\n",
       " '级末温度_6': 406.54999999999995,\n",
       " '级末比焓_6': -1.0,\n",
       " '级末理想比焓_6': -1.0,\n",
       " '级内等效流量_6': -1.0,\n",
       " '级段效率_6': -1.0,\n",
       " '级末压力_7': 50000.0,\n",
       " '级末温度_7': 354.95,\n",
       " '级末比焓_7': -1.0,\n",
       " '级末理想比焓_7': -1.0,\n",
       " '级内等效流量_7': -1.0,\n",
       " '级段效率_7': -1.0,\n",
       " '补水压力_1': 8830000.0,\n",
       " '补水温度_1': 808.15,\n",
       " '补水比焓_1': -1.0,\n",
       " '补水流量_1': 1.2,\n",
       " '补水位置_1': 3.0,\n",
       " '补水压力_2': -1.0,\n",
       " '补水温度_2': 353.15,\n",
       " '补水比焓_2': -1.0,\n",
       " '补水流量_2': 34.2,\n",
       " '补水位置_2': 3.0,\n",
       " '补水压力_3': 8830000.0,\n",
       " '补水温度_3': 808.15,\n",
       " '补水比焓_3': -1,\n",
       " '补水流量_3': 3.063,\n",
       " '补水位置_3': 2,\n",
       " '补水压力_4': -1.0,\n",
       " '补水温度_4': -1.0,\n",
       " '补水比焓_4': -1.0,\n",
       " '补水流量_4': -1.0,\n",
       " '补水位置_4': -1.0,\n",
       " '补水压力_5': -1.0,\n",
       " '补水温度_5': -1.0,\n",
       " '补水比焓_5': -1.0,\n",
       " '补水流量_5': -1.0,\n",
       " '补水位置_5': -1.0,\n",
       " '主蒸汽比焓': -1.0,\n",
       " '凝结水比焓': -1.0,\n",
       " '级末压力_8': -1.0,\n",
       " '级末温度_8': -1.0,\n",
       " '级内等效流量_8': -1.0,\n",
       " '级末比焓_8': -1.0,\n",
       " '级末理想比焓_8': -1.0,\n",
       " '级段效率_8': -1.0,\n",
       " '加热器位置_1': 1.0,\n",
       " '加热器位置_2': 2.0,\n",
       " '加热器位置_3': 3.0,\n",
       " '加热器位置_4': 4.0,\n",
       " '加热器位置_5': 5.0,\n",
       " '加热器位置_6': 6.0,\n",
       " '加热器位置_7': 7.0,\n",
       " '抽汽比焓_1': -1.0,\n",
       " '抽汽比焓_2': -1.0,\n",
       " '抽汽比焓_3': -1.0,\n",
       " '抽汽比焓_4': -1.0,\n",
       " '抽汽比焓_5': -1.0,\n",
       " '抽汽比焓_6': -1.0,\n",
       " '抽汽比焓_7': -1.0,\n",
       " '进口比焓_1': -1.0,\n",
       " '进口比焓_2': -1.0,\n",
       " '进口比焓_3': -1.0,\n",
       " '进口比焓_4': -1.0,\n",
       " '进口比焓_5': -1.0,\n",
       " '进口比焓_6': -1.0,\n",
       " '进口比焓_7': -1.0,\n",
       " '出口比焓_1': -1.0,\n",
       " '出口比焓_2': -1.0,\n",
       " '出口比焓_3': -1.0,\n",
       " '出口比焓_4': -1.0,\n",
       " '出口比焓_5': -1.0,\n",
       " '出口比焓_6': -1.0,\n",
       " '出口比焓_7': -1.0,\n",
       " '疏水比焓_1': -1.0,\n",
       " '疏水比焓_2': -1.0,\n",
       " '疏水比焓_3': -1.0,\n",
       " '疏水比焓_4': -1.0,\n",
       " '疏水比焓_5': -1.0,\n",
       " '疏水比焓_6': -1.0,\n",
       " '疏水比焓_7': -1.0,\n",
       " '供热抽汽比焓_1': -1.0,\n",
       " '供热抽汽比焓_2': -1.0,\n",
       " '排气比焓': -1,\n",
       " '锅炉给水比焓': -1}"
      ]
     },
     "metadata": {},
     "execution_count": 19
    }
   ],
   "source": [
    "import joblib \n",
    "joblib.load('2021-2-29.jl.z')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}